A CT scanner includes an x-ray tube supported by a rotating gantry, which is rotatably affixed to a stationary gantry. The x-ray tube emits radiation that traverses an examination region and a portion of a patient therein (which attenuates the radiation as a function of the radiodensity of the patient). A subject support supports the patient and is configured to position the patient in the examination region for scanning. A detector array disposed across the examination region, opposite the x-ray tube, detects radiation traversing the examination region and produces projection data indicative of the detected radiation. The projection data can be reconstructed to generate three dimensional (3D) volumetric image data indicative of the portion of the patient.
For a CT acquisition (e.g. axial or helical), generally, a surview is first performed. The surview is acquired with the rotating gantry at a static position (not rotating) and with the subject support moving in the z direction through the examination region. The resulting data is a two dimensional (2D) projection image of the scanned portion of the patient. The 2D projection image is used to generate a plan for the CT acquisition, including identifying tissue of interest to be scanned during the CT acquisition and the z-axis extent of the patient (i.e., zmin and zmax) of the CT acquisition based on the tissue of interest. The extent is typically determined by the technician at the console on the 2D projection image by positioning and overlaying a region of interest (ROI) box that covers the tissue of interest.
Once planned, the CT acquisition can be performed. The acquired data is reconstructed, producing the 3D volumetric image data. However, typically, only a subset of the reconstructed data, for example, the portion corresponding particularly to the tissue of interest is further processed, for instance, optimized for visual inspection. This subset often includes slices with a thickness that is larger than the slices in the original reconstructed 3D volumetric image data. Furthermore, the subset may include images in multiple orientations (i.e., sagittal, transversal, and/or coronal). The subset and the surview is formatted in accordance with the Digital Imaging and Communications in Medicine (DICOM) standard and stored in a Picture Archiving and Communications System (PACS). The original reconstructed data may not be stored, e.g., due to its size.
CT acquisitions of the same tissue at different moments in time have been compared to obtain information about the tissue. For example, such acquisitions have been utilized to visually observe and/or quantify physical changes (e.g., growth or shrinkage) in the geometry of a tumor or other tissue over time. However, in order for the obtained information to be diagnostically useful, the acquisition settings should be similar. By way of example, if, for instance, the tumor diameter is measured in a baseline image in a given CT slice, the follow-up image should have geometry such that there is a corresponding slice with respect to the tumor position. Otherwise a difference in size of the tumor in the two data sets may be incorrectly estimated.
Typically, there is a standard operating procedure for a given examination type in a radiology department that determines where to place the ROI boxes. Unfortunately, the variability to be observed in real clinical data is high and does not allow an easy accurate comparison of baseline and follow-up images. Furthermore, it is extremely tedious and time consuming to manually position the ROI boxes so as to reproduce a baseline examination with sufficient accuracy. Therefore, there is an unresolved need for approaches for planning a follow up CT acquisition of tissue of interest where the tissue of interest in the resulting images is well suited for comparison with the tissue of interest in the baseline images.